基于用户兴趣偏好度的音乐智能推荐系统设计分析  被引量:3

Design and analysis of music intelligent recommendation system based on user interest preference

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作  者:张利鸽[1] ZHANG Lige(Weinan Normal University,Weinan 714000,China)

机构地区:[1]渭南师范学院,陕西渭南714000

出  处:《电子设计工程》2022年第11期189-193,共5页Electronic Design Engineering

摘  要:为准确向用户推荐感兴趣的音乐,提升应用对象市场占有率,该文设计了由数据采集模块、离线数据处理模块和在线推荐模块共同组成的基于用户兴趣偏好度的音乐智能推荐系统。数据采集模块采集用户注册信息、对目标音乐的在线评分数据,并进行在线调查采集相关数据。离线数据处理模块以数据采集模块采集的数据为基础,构建POI关联图,以此为基础基于时间分析计算确定用户兴趣偏好度。在线推荐模块采用协同过滤推荐算法,针对不同用户需求为用户推荐符合其偏好的音乐。实验结果显示,该系统可准确向用户推荐感兴趣的音乐,将应用对象市场占有率提升至92.4%。In order to accurately recommend interesting music to users and increase the market share of application objects,an intelligent music recommendation system based on user interest preference is designed,which consists of data acquisition module,offline data processing module and online recommendation module.The data collection module collects user registration information,online scoring data of target music,and carries out online investigation to collect relevant data.The offline data processing module builds POI association graph based on the data collected by the data collection module,and determines the user’s interest preference degree based on time analysis and calculation.The online recommendation module adopts collaborative filtering recommendation algorithm to recommend music to users according to their preferences.The experimental results show that the system can accurately recommend the music of interest to the users,increasing the market share of the application objects to 92.4%.

关 键 词:兴趣偏好度 音乐推荐 数据采集 离线计算 关联时间 协同过滤 

分 类 号:TN01[电子电信—物理电子学]

 

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